“…Fuzzy set theory was introduced by L. Zadeh, as a new paradigm, which deals with certain types of uncertainty [3,4,17]. In the area of performance reliability, a number of performance issues must be addressed and investigated deeply using fuzzy set theory due to the characteristic of these problems.…”
Section: Proposed Algorithmmentioning
confidence: 99%
“…Assume that we have a shortage of information regarding the environment of the mobile agent-based system, in other words, the amount of information observed about the network is less than the total information [17]. This shortage of information is related to the failure rates of the communication links and processors (edges and vertices).…”
Section: Introductionmentioning
confidence: 99%
“…The uncertainty about failure rates force us to switch to another paradigm that deal with such kind of problem. It is the fuzzy reliability approach [3,4,6,11,17,20]. Uncertainty in this context leads to a possibility of a false estimation for the required reliability.…”
Section: Introductionmentioning
confidence: 99%
“…9. The failure rates of the processors and communication links are unknown, or are not know specifically due to several reasons: (i) Hardware components are in design phase, and limited data is available [3,17]; (ii) Error in recording or collecting data (human or machine errors); and (iii) Unexpected situations [20]. …”
mentioning
confidence: 99%
“…To estimate (1) under assumption (9), and to avoid any false estimation, we used the fuzzy reliability approach [3,4,6,11,17,20] instead of conventional reliability. The following sections illustrate the solution.…”
In this paper we explore the reliability of mobile agent-based systems under the assumption of uncertainty regarding the system's environment (network). The lack of information about the failure rates of processors and communications links make it hard to estimate the required reliability using the conventional approach. To solve this problem, a fuzzy approach is suggested and experiments are conducted through Monte Carlo simulation. The results show the robustness of the proposed approach.
“…Fuzzy set theory was introduced by L. Zadeh, as a new paradigm, which deals with certain types of uncertainty [3,4,17]. In the area of performance reliability, a number of performance issues must be addressed and investigated deeply using fuzzy set theory due to the characteristic of these problems.…”
Section: Proposed Algorithmmentioning
confidence: 99%
“…Assume that we have a shortage of information regarding the environment of the mobile agent-based system, in other words, the amount of information observed about the network is less than the total information [17]. This shortage of information is related to the failure rates of the communication links and processors (edges and vertices).…”
Section: Introductionmentioning
confidence: 99%
“…The uncertainty about failure rates force us to switch to another paradigm that deal with such kind of problem. It is the fuzzy reliability approach [3,4,6,11,17,20]. Uncertainty in this context leads to a possibility of a false estimation for the required reliability.…”
Section: Introductionmentioning
confidence: 99%
“…9. The failure rates of the processors and communication links are unknown, or are not know specifically due to several reasons: (i) Hardware components are in design phase, and limited data is available [3,17]; (ii) Error in recording or collecting data (human or machine errors); and (iii) Unexpected situations [20]. …”
mentioning
confidence: 99%
“…To estimate (1) under assumption (9), and to avoid any false estimation, we used the fuzzy reliability approach [3,4,6,11,17,20] instead of conventional reliability. The following sections illustrate the solution.…”
In this paper we explore the reliability of mobile agent-based systems under the assumption of uncertainty regarding the system's environment (network). The lack of information about the failure rates of processors and communications links make it hard to estimate the required reliability using the conventional approach. To solve this problem, a fuzzy approach is suggested and experiments are conducted through Monte Carlo simulation. The results show the robustness of the proposed approach.
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